An exploratory human study of superstable homogeneous lipiodol-indocyanine green formulation for precise surgical navigation in liver cancer.

The clinical applications of transcatheter arterial embolization (TAE) conversion therapy combined with hepatectomy have been severely restricted by ill-defined tumoral boundaries and miniscule hidden lesions. Fluorescent surgical navigation is a promising method for overcoming these barriers. However, sufficient delivery of the fluorescent probe into the tumor region after long-term TAE is challenging due to blockade of the tumor-supplying artery.

Learning to learn by yourself: Unsupervised meta-learning with self-knowledge distillation for COVID-19 diagnosis from pneumonia cases.

The goal of diagnosing the coronavirus disease 2019 (COVID-19) from suspected pneumonia cases, that is, recognizing COVID-19 from chest X-ray or computed tomography (CT) images, is to improve diagnostic accuracy, leading to faster intervention. The most important and challenging problem here is to design an effective and robust diagnosis model. To this end, there are three challenges to overcome: (1) The lack of training samples limits the success of existing deep-learning-based methods.

Resection and survival data from a clinical trial of glioblastoma multiforme-specific IRDye800-BBN fluorescence-guided surgery.

Supra-maximum surgical tumor resection without neurological damage is highly valuable for treatment and prognosis of patients with glioblastoma multiforme (GBM). We developed a GBM-specific fluorescence probe using IRDye800CW (peak absorption/emission, 778/795 nm) and bombesin (BBN), which (IRDye800-BBN) targets the gastrin-releasing peptide receptor, and evaluated the image-guided resection efficiency, sensitivity, specificity, and survivability. Twenty-nine patients with newly diagnosed GBM were enrolled.

Both activated and less-activated regions identified by functional MRI reconfigure to support task executions.

Introduction: Functional magnetic resonance imaging (fMRI) has become very important for noninvasively characterizing BOLD signal fluctuations, which reflect the changes in neuronal firings in the brain. Unlike the activation detection strategy utilized with fMRI, which only emphasizes the synchronicity between the functional nodes (activated regions) and the task design, brain connectivity and network theory are able to decipher the interactive structure across the entire brain. However, little is known about whether and how the activated/less-activated interactions are associated with the functional changes that occur when the brain changes from the resting state to a task state.